Latency-Aware Dynamic Resource Allocation Scheme for Multi-Tier 5G Network: A Network Slicing-Multitenancy Scenario
In 5G slice networks, the multi-tenant, multi-tier heterogeneous network will be critical in meeting the quality of service (QoS) requirement of the different slice use cases and in reduction of the capital expenditure (CAPEX) and operational expenditure (OPEX) of mobile network operators. Hence, 5G...
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9072146/ |
| _version_ | 1818932143982641152 |
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| author | Sunday Oladayo Oladejo Olabisi Emmanuel Falowo |
| author_facet | Sunday Oladayo Oladejo Olabisi Emmanuel Falowo |
| author_sort | Sunday Oladayo Oladejo |
| collection | DOAJ |
| description | In 5G slice networks, the multi-tenant, multi-tier heterogeneous network will be critical in meeting the quality of service (QoS) requirement of the different slice use cases and in reduction of the capital expenditure (CAPEX) and operational expenditure (OPEX) of mobile network operators. Hence, 5G slice networks should be as flexible as possible to accommodate different network dynamics such as user location and distribution, different slice use case QoS requirements, cell load, intra-cluster interference, delay bound, packet loss probability, and service level agreement (SLA) of mobile virtual network operators (MVNO). Motivated by this condition, this paper addresses a latency-aware dynamic resource allocation problem for 5G slice networks in a multi-tenant, multi-tier heterogeneous environment, for efficient radio resource management. The latency-aware dynamic resource allocation problem is formulated as a maximum utility optimisation problem. The optimisation problem is transformed and the hierarchical decomposition technique is adopted to reduce the complexities in solving the optimisation problem. Furthermore, we propose a genetic algorithm (GA) intelligent latency-aware resource allocation scheme (GI-LARE). We compare GI-LARE with the static slicing (SS) resource allocation; the spatial branch and bound-based scheme; and, an optimal resource allocation algorithm (ORA) via Monte Carlo simulation. Our findings reveal that GI-LARE outperformed these other schemes. |
| first_indexed | 2024-12-20T04:27:48Z |
| format | Article |
| id | doaj.art-371fd9002d854fc584e8bc25005610fa |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-20T04:27:48Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-371fd9002d854fc584e8bc25005610fa2022-12-21T19:53:27ZengIEEEIEEE Access2169-35362020-01-018748347485210.1109/ACCESS.2020.29887109072146Latency-Aware Dynamic Resource Allocation Scheme for Multi-Tier 5G Network: A Network Slicing-Multitenancy ScenarioSunday Oladayo Oladejo0https://orcid.org/0000-0001-9573-5189Olabisi Emmanuel Falowo1https://orcid.org/0000-0003-4329-4152Department of Electrical Engineering, University of Cape Town, Rondebosch, South AfricaDepartment of Electrical Engineering, University of Cape Town, Rondebosch, South AfricaIn 5G slice networks, the multi-tenant, multi-tier heterogeneous network will be critical in meeting the quality of service (QoS) requirement of the different slice use cases and in reduction of the capital expenditure (CAPEX) and operational expenditure (OPEX) of mobile network operators. Hence, 5G slice networks should be as flexible as possible to accommodate different network dynamics such as user location and distribution, different slice use case QoS requirements, cell load, intra-cluster interference, delay bound, packet loss probability, and service level agreement (SLA) of mobile virtual network operators (MVNO). Motivated by this condition, this paper addresses a latency-aware dynamic resource allocation problem for 5G slice networks in a multi-tenant, multi-tier heterogeneous environment, for efficient radio resource management. The latency-aware dynamic resource allocation problem is formulated as a maximum utility optimisation problem. The optimisation problem is transformed and the hierarchical decomposition technique is adopted to reduce the complexities in solving the optimisation problem. Furthermore, we propose a genetic algorithm (GA) intelligent latency-aware resource allocation scheme (GI-LARE). We compare GI-LARE with the static slicing (SS) resource allocation; the spatial branch and bound-based scheme; and, an optimal resource allocation algorithm (ORA) via Monte Carlo simulation. Our findings reveal that GI-LARE outperformed these other schemes.https://ieeexplore.ieee.org/document/9072146/Network slicingmulti-tiermulti-tenancyresource allocation |
| spellingShingle | Sunday Oladayo Oladejo Olabisi Emmanuel Falowo Latency-Aware Dynamic Resource Allocation Scheme for Multi-Tier 5G Network: A Network Slicing-Multitenancy Scenario IEEE Access Network slicing multi-tier multi-tenancy resource allocation |
| title | Latency-Aware Dynamic Resource Allocation Scheme for Multi-Tier 5G Network: A Network Slicing-Multitenancy Scenario |
| title_full | Latency-Aware Dynamic Resource Allocation Scheme for Multi-Tier 5G Network: A Network Slicing-Multitenancy Scenario |
| title_fullStr | Latency-Aware Dynamic Resource Allocation Scheme for Multi-Tier 5G Network: A Network Slicing-Multitenancy Scenario |
| title_full_unstemmed | Latency-Aware Dynamic Resource Allocation Scheme for Multi-Tier 5G Network: A Network Slicing-Multitenancy Scenario |
| title_short | Latency-Aware Dynamic Resource Allocation Scheme for Multi-Tier 5G Network: A Network Slicing-Multitenancy Scenario |
| title_sort | latency aware dynamic resource allocation scheme for multi tier 5g network a network slicing multitenancy scenario |
| topic | Network slicing multi-tier multi-tenancy resource allocation |
| url | https://ieeexplore.ieee.org/document/9072146/ |
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